基于XRF与RBF神经网络的锌浸出渣有价组分精准定量分析研究

锌冶炼浸出渣是湿法炼锌工艺产出的冶炼固废渣,占锌冶炼固废产出总量的75％ 以上,因含有Zn,Cu,Pb,Ag,Cd和As等多种有价金属元素,其资源化利用潜力巨大.然而由于其成分含量不稳定,检测精度不足等原因,导致关键元素的资源转化效率难以保证,因此对浸出渣关键资源组分的精准定量分析在锌冶炼行业绿色发展方面具有重大意义....     

基于RBF网络的断路器电流自适应保护研究

针对传统断路器电流保护方法存在受系统运行方式影响、整定困难、智能化低等问题,本文提出了基于RBF的断路器电流自适应保护算法,并给出了算法的模型。该算法融合了RBF神经网络的故障检测和电流自适应保护。首先通过RBF网络检测负载线路的电流故障,然后用电流自适应算法进行保护。在对神经网络进行训练时,利用PSO算法对RBF神经网络的参数进行优化以此来提高网络的泛化能力和学习能力;然后采用优化后的PSO-RBF神经网络对电流故障进行诊断。实验表明,该算法较大地提高了断路器智能化管理水平。     

Detection of Cholangiocarcinoma with Fourier Transform Infrared Spectroscopy and Radial Basis Function Neural Network Classification

The aim of this study was to explore the possibility of applying Fourier transform infrared(FTIR) spectroscopy as a medical diagnostic tool based on a neural network classifier for detecting and classifying cholangiocarcinoma. A total of 51 cases of bile duct tissues were obtained and later characterized by FTIR spectroscopy prior to pathological diagnosis. The criteria for classification included 30 parameters for each FTIR spectra, including peak position(P), intensity(I) and full width at half-maximum(FWHM), were measured, calculated and subsequently compared against the normal and cancer groups. The FTIR spectra were classified by the radial basis function(RBF) network model. For establishing the RBF, 23 cases were used to train the RBF classifier, and 28 cases were applied to validate the model. Using the RFB model, nine parameters were observed to be pronouncedly different between cancerous and normal tissue, including I₁₆₄₀, I₁₅₅₀, I₁₄₆₀, I₁₄₀₀, I₁₂₅₀, I₁₁₂₀, I₁₀₈₀, I₁₀₄₀ and P₁₀₄₀. In the RBF training classification, the accuracy, sensitivity, and specificity of diagnosis were 82.6%, 80.0%, and 84.6%, respectively. While validating the classification, the accuracy, sensitivity, and specificity of diagnosis were 78.6%, 75.0%, and 81.2%, respectively. The results suggest that FTIR spectroscopy combined with neural network classifier could be applied as a medical diagnostic tool in cholangiocarcinoma diagnosis.     

基于RBF插值技术的CFD/CSD非线性耦合分析方法研究

基于非结构混合网格的N-S方程求解器和结构柔度影响系数法,发展了一种考虑气动、结构非线性的基于RBF插值技术CFD/CSD耦合分析方法,适用于解决现代大展弦比飞机的非线性静气动弹性问题。该方法采用时间相关法（即求解非定常方程组,用长时间的渐近解趋于定常状态）求解静气弹分析时的定常流动。考虑大展弦比飞机结构变形问题为大变形小应力问题,在利用柔度系数法求解结构方程时,假设每次求解结构方程时应力与应变为线性关系,整体静气弹分析过程为非线性关系,因此每次求解结构方程时要更新柔度影响系数矩阵。在非定常N-S方程每求解一个时间步耦合一次结构有限元分析,由于结构有限元分析的时间相对于气动分析时间是很短的,所以这种方法实际上近似使用了一次求解非定常气动力的时间完成了整个静气动弹性分析的过程。对于气动网格与结构有限元网格不一致性,本文采用径向基函数（RBF）插值方法中的TPS方法进行结构弹性变形和气动载荷插值,采用虚功原理完成气动载荷数据交换。为了节省气弹分析时间,采用动网格方法对气动网格进行更新,本文基于RBF插值方法发展一种适用于混合网格（四面体、三棱柱、金字塔和六面体）变形的动网格方法,可以保证附面层网格的质量与分布从而准确模拟其流动。利用该方法对M6机翼、DLR-F6翼身组合体和某大型客机机翼进行了静气动弹性特性分析,结果验证了本文开发的非线性CFD/CSD耦合分析方法的可行性、精确性和高效性。     

A high‐order upwind control‐volume method based on integrated RBFs for fluid‐flow problems

This paper is concerned with the development of a high‐order upwind conservative discretization method for the simulation of flows of a Newtonian fluid in two dimensions. The fluid‐flow domain is discretized using a Cartesian grid from which non‐overlapping rectangular control volumes are formed. Line integrals arising from the integration of the diffusion and convection terms over control volumes are evaluated using the middle‐point rule. One‐dimensional integrated radial basis function schemes using the multiquadric basis function are employed to represent the variations of the field variables along the grid lines. The convection term is effectively treated using an upwind scheme with the deferred‐correction strategy. Several highly non‐linear test problems governed by the Burgers and the Navier–Stokes equations are simulated, which show that the proposed technique is stable, accurate and converges well. Copyright © 2010 John Wiley & Sons, Ltd.     

交通流灰色RBF网络非线性组合预测方法

针对智能交通系统的开发,提出一种基于灰色GM(1,1)模型和RBF网络非线性组合的短时交通流预测方法.该方法采用三层结构的RBF网络将两种单一预测方法(灰色GM(1,1)模型和RBF网络)进行了非线性组合.利用实测数据对组合方法进行了仿真实验,结果表明:非线性组合模型的预测准确性高于单独的RBF网络预测的准确性;组合模型发挥了两种单一方法各自的优势,是短时交通流预测的有效方法.     

用RBF神经网络确定上海股市的分形维数

从预测能力的角度采用径向基函数（radial basis function，简称RBF）神经网络方法计算我国上海股票市场的分形维数，并通过RBF神经网络的实验，得到上海股市的最小嵌入维数为6，验证了股市分形维数在2-3之间，从而进一步确定了我国上海股票市场是一个具有混沌现象的系统，最后探讨了利用股票市场的混沌特性进行短期预测的效果的可行性。     

Numerical solution of the nonlinear Klein–Gordon equation using radial basis functions

The nonlinear Klein–Gordon equation is used to model many nonlinear phenomena. In this paper, we propose a numerical scheme to solve the one-dimensional nonlinear Klein–Gordon equation with quadratic and cubic nonlinearity. Our scheme uses the collocation points and approximates the solution using Thin Plate Splines (TPS) radial basis functions (RBF). The implementation of the method is simple as finite difference methods. The results of numerical experiments are presented, and are compared with analytical solutions to confirm the good accuracy of the presented scheme.     

Numerical study of radial basis function interpolation for data transfer across discontinuous mesh interfaces

Allowing discontinuous or non‐matching mesh spacing across zonal interfaces within a computational domain offers many advantages, particularly in terms of easing the mesh generation process, reduction of required mesh densities, and relative motion between mesh zones. This paper presents a numerical study of a universal method for interpolating solution data across such interfaces. The method utilises radial basis functions (RBFs) for n‐dimensional volume interpolation, and treats the available solution data points simply as arbitrary clouds of points, eliminating all connectivity requirements and making it applicable to a wide range of computational problems. Properties of the developed meshless interface interpolation are investigated using analytic functions, and three issues are considered: the achievable order of spatial accuracy of the RBF interpolation alone and comparison with a variable order polynomial; the effect of a combined RBF and polynomial interpolation; and the ability of the method to recover frequency content. RBF interpolation alone is shown to achieve fourth‐order to sixth‐order spatial accuracy in one and two dimensions, and in three dimensions, using a small number of data points, third‐order and above is achievable even for a 3 : 1 discontinuous cell spacing ratio, that is a 27 : 1 volume ratio, across the interface. Hence, it is inefficient to include polynomial terms, since improving on the RBF spatial accuracy results in a significant increase in the system size and deterioration in conditioning. It is also shown that only five points per wavelength are required to capture both frequency and amplitude content of periodic solutions to less than 0.01% error.Copyright © 2013 John Wiley & Sons, Ltd.     

EMD结合RBF神经网络新混合模型及股指期货价格预测

中国近4年才成立的股指期货市场价格呈现出非平稳、非线性的信号特征,传统的预测方法无法对长相关序列进行精确预测.将EMD与RBF相结合,建立了一种新的预测方法对我国股指期货日结算价格进行预测.结果显示本模型将原本具有长相关性质的原始序列分解为若干个短相关性质的不同频带,解决了原始序列随机性强,以及因相邻频带的干扰而造成的系统动力信息反映不足的缺陷;并与其他预测模型进行比较,显示出较高的预测精度.